Principal Scientist, R&D Data, Data Science & Artificial Intelligence, Immunology

Johnson & Johnson

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Cambridge, MASpring House, PATitusville, NJRaritan, NJSan Diego, CA
Salary
$117,000–$201,250 / yr
Posted
11 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $186k
This role $159k
$103k most similar roles pay here $249k

This role pays less than 68% of similar roles. Most pay $141,300–$231,550 — the shaded band above. At the midpoint, this role pays about $159k versus about $186k for comparable roles.

Based on 240 similar postings.

Employer

About Johnson & Johnson

Johnson & Johnson is a multinational corporation operating in three main segments: consumer health products, pharmaceuticals, and medical devices, known for brands like Tylenol, Band-Aid, and Janssen. Industry: Pharmaceuticals & Medical Devices

Johnson & Johnson currently has 46 open roles on FindRole.

Listed pay typically runs $117,000–$201,250 across 42 roles with salary data.

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At a glance

TL;DR · Principal Scientist, R&D Data, Data Science & Artificial Intelligence, Immunology

Principal Scientist, R&D Data, Data Science & Artificial Intelligence - Immunology will join the Immunology Therapeutic Area team to design, evaluate, and execute data science, digital health, and AI strategies. The role involves partnering with cross-functional stakeholders to identify and advance technology-enabled opportunities that improve research execution and decision-making across the portfolio. Key responsibilities include mapping scientific workflows for automation, developing roadmaps from pilot to scale, and evaluating emerging technologies like generative AI and agentic workflows. The candidate will work with diverse data assets including imaging, clinical, real-world, biomarker, and omics data. Required skills include experience in pharmaceutical R&D or biotechnology, as well as proficiency with Python, R, SQL, and cloud platforms. This role solves complex research challenges by translating scientific needs into practical, scalable solutions within the immunology therapeutic area to enhance drug development outcomes.

What you'll do

  • Define and execute high-impact data science, digital health, and AI initiatives aligned with Immunology R&D objectives.
  • Translate scientific needs into practical solutions using data science, analytics, and artificial intelligence.
  • Map and analyze scientific workflows to identify opportunities for automation and process improvements.
  • Develop roadmaps to move data science use cases from initial pilot stages to large-scale implementation.
  • Evaluate and pilot emerging technologies including generative AI, agentic workflows, and advanced analytics.
  • Partner with engineering teams to build scalable, governed, and interoperable data and digital capabilities.
  • Analyze diverse datasets including clinical, real-world, imaging, and biomarker data to support R&D decisions.
  • Communicate technical recommendations and high-quality materials to leadership forums to support strategic decision-making.

What we're looking for

  • Master's degree in engineering, mathematics, or a related scientific discipline is required.
  • A PhD is considered a preferred qualification for this role.
  • At least 4 years of relevant experience in pharmaceutical R&D, biotechnology, healthcare, data science, digital health, AI, or analytics is required.
  • Demonstrated ability to work effectively in cross-functional and matrixed environments.
  • Experience translating scientific or business needs into practical data, analytics, digital health, or AI-enabled solutions.
  • Demonstrated experience assessing and applying emerging AI technologies, including generative AI and agentic systems, to address various challenges.
  • Strong problem-solving, communication, organizational, and stakeholder engagement skills are required.
  • Familiarity with healthcare, clinical, imaging, digital health, biomarker, or real-world data is required.

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